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Data warehouse designers often ignore the specific needs of an OLAP database. In this session, John will outline the best ways to optimise your relational database to support your multidimensional OLAP cubes

Power BI offers new features for creating dashboards on the cloud. In this session, you will learn how to create data models, display visualizations and synchronize cloud data with on premise data sources.

Do you need an OLAP database? Do you know how the data changed over time?
Do you need an OLTP database? Do you need to write, never block and never lose a change?
Then Temporal Databases tick those boxes and are a simple solution to these problems.

Each of the default SSAS client tools (Pivot Tables, SSRS, Power BI etc.) have strengths, but numerous limitations. See how XLCubed extends business users abilities in reporting, dashboards & data discovery, in any version of of SSAS & Office.

This session goes beyond the classical star schema modeling, exploring new techniques to model data with Power Pivot and SSAS Tabular. You will see how brute-force power in DAX allows different data models than those used in SSAS Multidimensional

In this session Pyramid analytics will show how to use BI Office to easily build an adhoc Analysis Services Tabular Edition analytic data set and perform associative analysis using the unique features of BI Office.

This session targets SSAS developers that are already dealing with complex security solutions on a regular basis and want to get more insights on what actually happens inside SSAS when the different kinds of security are applied to their model.

Learn how XLCubed unlocks the value of Multi-dimensional and Tabular SSAS and SQL for power users in Excel; providing pixel perfect delivery of reporting, dashboards for both Web and Mobile and with or without SharePoint.

In this session we'll look at the structure and basics of MDX, the Multi Dimensional query eXpression language for querying Analysis Services OLAP cubes. We'll start at the beginning, so no previous experience necessary.

Mark will explain the use cases for Analysis Services, illustrate how it improves performance for large data sets and eases report writing, and will go through a practical example of building a first Analysis Services solution

In this session we’ll look at a number of different data scenarios and explore ways of remodelling the data to optimise it for cubes and MDX. Sometimes a small ETL change can have a dramatic impact on the cube's functionality and simplicity.

In this session, we will analyze the way DAX solves filtering. Starting from simple queries, we will follow the steps DAX does with the filter context, discovering the internals of the query engine of DAX.

Processing of SSAS OLAP databases can be a tricky business, particularly when it comes to incremental processing of dimensions. John will give you real life examples of why certain approaches work and others do not.

Compare and contrast how multidimensional and tabular achieve the same end result in quite different ways. Features covered can be used in a broad range of scenarios (not only currency conversion), adding valuable knowledge to your SSAS arsenal.

This session will discuss what a modern strategy for data warehousing can be in this era, considering how the use of technologies like PowerPivot or Analysis Services Tabular affect the way you should model your data.

PowerPivot is a breakthrough for self-serve BI but is not easily deployed in the enterprise. Join us for this fast-paced, technical demonstration on how to upgrade PowerPivot into secure and scalable Analysis Services tabular cubes

In this session, we are going to explain and test different DW features in SQL Server 2012, including star join optimization through bitmap filters, table partitioning, window functions, columnstore indices and more.

In this session we'll understand the best practices of using this new technology. What exactly is it good for? When to use it and when NOT to?
Migration, Security, Administration and other tips and tricks.

The Microsoft BI stack has a number of tools for data visualization - Excel, Power View, native Reporting Services, and Performance Point. Come see each visualization applied to the new tabular model in Analysis Services.

Users love flexible analytics but hate to wait for the data to be loaded into a traditional data warehouse. John will describe how to build an infrastructure to support real-time loading of your OLAP cubes so your user's get exactly what they want

Most of us use Excel in our Daily work, but are you familiar with the Business Intelligence features in Excel? In this session we'll look at some of the most common and useful BI features in Excel 2010 and discuss limitations and best practices.

In this session you will see how to create a BISM Tabular data model from scratch, providing the required metadata in order to improve user experience navigating the data model by using client tools like Excel PivotTable and Power View.

But were afraid to ask.
Pyramid Analytics burst onto the Microsoft BI scene with not only a full roadmap for ProClarity users, but also with cube driven dashboards that offer rich functionality – yet are easy to design and deploy by business users.

Learn how to monitor Analysis Services with SQL Sentry Performance Advisor. Get tips on best practices, monitoring counters and options plus improve your understanding of how Analysis Services uses memory and where it differs from SQL Server.

This session will do a brief overview of Analysis Services 2012 performance topics, and drill into some common methods for investigating performance issues. The talk will be adjusted based on the audience interests.

Snapshots without snapshots...is that possible? Take a "Classic" snapshot fact table, add some temporal data theory and you'll get a new fact table than can store snapshot data without doing snapshots. A life saver when you have a lot of data.

Reporting Services is a powerful tool that can make designing reports a snap...most of the time. Design format starts with your report query. Take your queries to the next level with MDX concepts to conquer the trickiest report layouts.

SQL Server Code Name Denali Reporting Services will include Project Crescent for visualizing, interacting with and presenting data. Project Crescent. Come to this session to see how to make the most of this new tool.

Master Data Services has been given an overhaul in Denali, including a new Excel add-in and modified web front-end. Come to this session to see how MDS can be used to give greater control and process to your BI/DW dimension management.

This talk looks at MDX and DAX, examining their similarities and differences. It won’t turn you into an expert in either but it will help you to decide, given your particular career plans, if either or both are worth learning.

In this session we will introduce the new modeling capabilities of Vertipaq, showing how the same scenarios can be modeled in both Multidimensional (MOLAP) and Tabular (Vertipaq), looking at how to enable your data warehouse to support both.

With Excel 2010 it is finally possible to modify data in a SSAS cube, without using any macros or third party add-ins. This opens for a lot of common business scenarios like budgeting and planning directly from Excel 2010.

This session will show how to use DMVs (data management views) to query the OLAP cube structure, and then use SSRS to create a set of interactive reports including the BUS matrix, and using spatial data to generate automated star schemas.

PowerPivot can be a great troubleshooting / performance tuning tool for a dba besides just loading all the data in a database and start querying. I'll show the pro's and cons of PowerPivot while trying work with waitstats, profiler data etc.

The origins, use and evolution of OLAP software over the last 25 years. This is a personal view (not a history lesson) from an experienced BI practitioner who has used a variety of OLAP software, such as, SQL Server Analysis Services since graduating in 1985.

The Microsoft SQL Server provides a complete library of programmatically accessed objects for all Business Intelligence relevant services. With this set of functions almost any customer challenge can be solved without the need to purchase additional products. This possibility is often underestimated in projects. The session will explain the hidden power of using the Microsoft APIs to build BI middleware solutions for enterprise customers.

This session will investigate using Stream Insight, SQL Server and Analysis Services to provide an example framework to monitor cube usage as well as suggest a mechanism for highlighting areas for performance and security enhancements.

MDX Studio can be used to analyze complex MDX expressions, monitor performance characteristics of MDX queries and get insight into how MDX interacts with other UDM features such as attribute relationships.

A step-by-step demo on BIDS of how to build an SSAS cube (DB) from an operational system (normalized database) such as Operational Data Store (ODS) or directly from the transactional business system, without building a star/snowflake schema Data Warehouse/Mart first.

This session will introduce you to the core components required to set up and create a cube in SQL Server Analysis services. consideration is given to SQL Server 2005 and SQL Server 2008
to be considered for Friday

John will introduce you to Analysis Services 2008, demonstrate browsing cubes with Excel 2007, deploying dashboards in SharePoint built using Excel Services and demonstrate how PerformancePoint Services can add the glitz to your BI project.

Among many of its functions, MDX language has one special set function - Axis() function. That function allows creation of calculated measures that are context aware and, if wanted, don't need to refer to any dimension or hierarchy in the cube. In other words, such measures are universal or independant, which means they can be used in any MDX query.
In this session we will present such measures and explain how they work. We'll also show the way how to design them for various scenarios and discuss their potentials and weaknesses.
Previous experience in writing MDX queries is recommended.